SaaS Metrics & Revenue Intelligence Platform

I designed and built a production-ready SaaS revenue intelligence platform focused on subscription analytics, retention modeling, and growth forecasting. The system provides CEO-level insights beyond static reporting and transforms raw transactional data into strategic business metrics. Core features include full MRR decomposition (New, Expansion, Contraction, Churned MRR), ARR, NRR, GRR, ARPA, CAC, LTV, and LTV:CAC. All metrics are calculated server-side from live database records with strict multi-tenant isolation and real-time recalculation. The platform includes an MRR Waterfall view for revenue reconciliation, cohort retention analysis, activation funnel tracking, and a 6–12 month MRR forecast engine based on historical churn and expansion rates. A Simulation Mode allows sandbox scenario planning without modifying production data. Additional features include KPI drill-down breakdowns, CSV import with validation, webhook-ready ingestion endpoints, data health monitoring, caching with invalidation, and role-based access control. The project was engineered with scalability and correctness in mind, ensuring accurate financial modeling and investor-ready reporting.